Update app.py

app.py

@@ -3,6 +3,7 @@ import requests
 import openai
 from io import BytesIO
 from PIL import Image
+import random
 
 # Set page configuration as the first Streamlit command
 st.set_page_config(page_title="Eco-Symphony", page_icon="🌱", layout="centered")
@@ -59,6 +60,34 @@ if "image_bytes" not in st.session_state:
 if "ngos" not in st.session_state:
     st.session_state.ngos = []
 
+# Function to generate daily challenges using GPT
+def generate_daily_challenges() -> list:
+    prompt = "Give me 5 small, easy-to-do eco-friendly daily challenges that can be completed in a day."
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": prompt}],
+        max_tokens=100,
+        temperature=0.8
+    )
+    challenges = response.choices[0].message['content'].strip().split("\n")
+    return [challenge.strip() for challenge in challenges if challenge.strip()]
+
+# Function to fetch endangered species based on user's city
+def fetch_endangered_species(city: str) -> dict:
+    prompt = f"Provide details of an endangered species in {city}, including its name, image description, and current population."
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": prompt}],
+        max_tokens=150,
+        temperature=0.8
+    )
+    response_content = response.choices[0].message['content'].strip()
+    try:
+        return eval(response_content)  # Assuming the response is a JSON-like structure
+    except Exception as e:
+        st.error(f"Error parsing endangered species data: {e}")
+        return {}
+
 # Function to fetch weather data
 def fetch_real_data(city: str) -> dict:
     weather_url = f'https://api.openweathermap.org/data/2.5/weather?q={city}&appid={OPENWEATHER_API_KEY}&units=metric'
@@ -124,65 +153,76 @@ def generate_image(description: str) -> bytes:
         return None
     return response.content
 
-# Function to fetch NGOs using OpenAI
-def fetch_nearby_ngos_with_openai(city: str, interests: list) -> list:
-    prompt = (
-        f"List NGOs near {city} that focus on {', '.join(interests)}. "
-        "Provide the names, locations, and focus areas in JSON format as a list of dictionaries."
-    )
-    response = openai.ChatCompletion.create(
-        model="gpt-3.5-turbo",
-        messages=[{"role": "user", "content": prompt}],
-        max_tokens=200,
-        temperature=0.7
-    )
-    response_content = response.choices[0].message['content'].strip()
-    
-    try:
-        ngo_list = eval(response_content)
-        if isinstance(ngo_list, list) and all(isinstance(ngo, dict) for ngo in ngo_list):
-            return ngo_list
-        else:
-            st.error("Unexpected response format. Could not parse NGO data.")
-            return []
-    except Exception as e:
-        st.error(f"Error fetching NGO data: {e}")
-        return []
+# Main daily challenges section
+def daily_challenges_section(city):
+    st.subheader("🏆 Daily Challenges")
 
-# Streamlit UI
+    # Points counter
+    if 'points' not in st.session_state:
+        st.session_state['points'] = 0
+    
+    st.markdown(f"<h2 style='text-align: center;'>💰 Points: {st.session_state['points']}</h2>", unsafe_allow_html=True)
+
+    # Generate or load daily challenges
+    if 'daily_challenges' not in st.session_state:
+        st.session_state['daily_challenges'] = generate_daily_challenges()
+
+    # Create a checkable list for the challenges
+    completed_challenges = []
+    for i, challenge in enumerate(st.session_state['daily_challenges']):
+        if st.checkbox(challenge, key=f"challenge_{i}"):
+            completed_challenges.append(i)
+
+    # Update points based on completed challenges
+    st.session_state['points'] = len(completed_challenges) * 10  # Example: 10 points per challenge
+
+    # Check if all challenges are completed
+    if len(completed_challenges) == len(st.session_state['daily_challenges']):
+        st.success("All challenges completed! 🎉 You've unlocked the secret section!")
+
+        # Fetch endangered species data for the user's city
+        species_data = fetch_endangered_species(city)
+        if species_data:
+            st.subheader("🦋 Endangered Species Unlocked!")
+            st.write(f"**Species**: {species_data.get('name', 'Unknown')}")
+            st.write(f"**Population**: {species_data.get('population', 'Unknown')}")
+            st.write(f"**Description**: {species_data.get('description', 'No description available')}")
+
+            # Generate an image of the endangered species
+            image_description = f"Generate an image of the endangered species: {species_data.get('name', 'Unknown')}"
+            species_image_bytes = generate_image(image_description)
+            if species_image_bytes:
+                species_image = Image.open(BytesIO(species_image_bytes))
+                st.image(species_image, caption=f"Endangered Species: {species_data.get('name', 'Unknown')}", use_column_width=True)
+
+# Add this to your Streamlit UI where appropriate
 st.title("🌿 Eco-Symphony 🎶")
-st.write("Enter a city to explore real-time environmental data, generate AI-created music, and see an AI-generated image based on the story.")
+st.write("Enter a city to explore real-time environmental data, complete daily challenges, and unlock hidden content!")
 
 city = st.text_input("Enter City Name:", placeholder="Type the name of a city...")
 
-if st.button("Generate Environmental Data, Music, and Image"):
+if city:
+    # Other sections of the app (weather data, music, etc.)
     st.session_state.real_data = fetch_real_data(city)
     if st.session_state.real_data:
-        # Generate narrative and mood
         narrative = create_narrative(city, st.session_state.real_data)
         mood = determine_mood(st.session_state.real_data)
-        
-        # Generate AI story
         st.session_state.story = generate_story_with_ai(narrative, mood)
-
-        # Generate Music and Image Based on Story and Mood
         music_description = f"{mood} mood with {st.session_state.real_data['weather_condition'].lower()} weather"
         st.session_state.music_bytes = generate_music(music_description)
         st.session_state.image_bytes = generate_image(st.session_state.story)
-
-# Display Music and Image at the Top
-if st.session_state.music_bytes:
-    st.subheader("🎶 Generated Music")
-    st.audio(BytesIO(st.session_state.music_bytes), format="audio/wav")
-
-if st.session_state.image_bytes:
-    st.subheader("🖼️ Generated Image")
-    st.image(Image.open(BytesIO(st.session_state.image_bytes)), caption="Generated Image based on Story", use_column_width=True)
-
-# Display Environmental Narrative and Data
-if st.session_state.real_data:
+    
+    # Display generated music and image at the top
+    if st.session_state.music_bytes:
+        st.subheader("🎶 Generated Music")
+        st.audio(BytesIO(st.session_state.music_bytes), format="audio/wav")
+    
+    if st.session_state.image_bytes:
+        st.subheader("🖼️ Generated Image")
+        st.image(Image.open(BytesIO(st.session_state.image_bytes)), caption="Generated Image based on Story", use_column_width=True)
+    
+    # Display the narrative and data
     st.subheader("📜 Environmental Narrative")
-    narrative = create_narrative(city, st.session_state.real_data)
     st.write(narrative)
     
     st.subheader("📊 Real Weather Data")
@@ -190,29 +230,9 @@ if st.session_state.real_data:
     st.write("Humidity (%):", st.session_state.real_data.get("humidity", "Data not available"))
     st.write("Weather Condition:", st.session_state.real_data.get("weather_condition", "Data not available"))
 
-if st.session_state.story:
-    st.subheader("🌈 AI-Generated Story")
-    st.write(st.session_state.story)
-
-# Get User's Environmental Interests
-st.subheader("🌍 Get Involved!")
-st.write("Choose your areas of interest for saving the environment:")
-interests = st.multiselect(
-    "Select Areas of Interest:",
-    ["Afforestation", "Water Conservation", "Biodiversity Protection", "Recycling", "Climate Change Awareness"]
-)
-
-if st.button("Find Nearby NGOs"):
-    if interests:
-        st.session_state.ngos = fetch_nearby_ngos_with_openai(city, interests)
-    else:
-        st.warning("Please select at least one area of interest.")
-
-# Display NGO information
-if st.session_state.ngos:
-    st.subheader("🌟 NGOs Near You")
-    for ngo in st.session_state.ngos:
-        st.write(f"**{ngo.get('name', 'Unknown NGO')}**")
-        st.write(f"📍 Location: {ngo.get('location', 'Unknown Location')}")
-        st.write(f"🌱 Focus Area: {ngo.get('focus', 'Unknown Focus Area')}")
-        st.write("---")
+    if st.session_state.story:
+        st.subheader("🌈 AI-Generated Story")
+        st.write(st.session_state.story)
+
+    # Display daily challenges section
+    daily_challenges_section(city)